Principal Engineer, Data Platform
About The Position
AlphaSense is moving its large-scale, Kubernetes-native microservices platform to a cell-based architecture, with each cell operating as an independent deployment. The Principal Engineer, Data Platform will help set the technical direction for the Data Platform and build capabilities that allow engineering teams to build, run, and scale storage without requiring every team to become an expert in each underlying system. The data ecosystem includes Vespa, MongoDB, ClickHouse, Redis, ScyllaDB, PostgreSQL, Temporal, and Kafka. A central focus of the role is enabling large-scale data migrations so data can be created, moved, split, and rebalanced across cells and geographies as the architecture is rolled out. The role also enables teams to own and operate their storage, preferably using managed solutions where suitable, while establishing the platform, standards, and tooling needed to do so safely. The position owns the reliability and scalability of the Data Platform and works closely with Cloud Platform, SRE, and DevEx teams.
Requirements
- Deep hands-on experience designing and operating data platforms and storage systems.
- Production experience at large scale with storage systems such as MongoDB, ClickHouse, Redis, or PostgreSQL.
- Cloud-native data storage experience, including managed data services on AWS.
- Strong background in Kubernetes and containers.
- Track record of designing and operating large-scale data migrations, including live migrations.
- Experience with cell-based, multi-tenant, or multi-region architectures.
- Experience building platforms and tooling used by other engineers, and comfort with a model in which engineers own their storage and run what they build.
- Demonstrated ability to land significant changes in code owned by other teams.
- Record of identifying data scalability and reliability limits before they become incidents.
- Ability and desire to design, lead, influence, and deliver ambitious technical roadmaps.
Nice To Haves
- Experience running storage systems on top of Kubernetes.
- Experience building control planes with Crossplane.
- Experience with private, isolated, on-premises, or air-gapped deployments.
Responsibilities
- Help set the architecture and roadmap for the Data Platform and its storage ecosystem.
- Build capabilities for large-scale data migrations across cells, regions, and geographies, including tooling to move, split, validate, and roll back data with minimal downtime.
- Enable product teams to provision, operate, and scale their storage through self-service capabilities.
- Drive data-layer changes required by cell-based architecture, including data placement, tenant routing, replication, and isolation.
- Define and apply a managed-first approach, choosing managed services where suitable and building and operating self-managed systems only when there is a clear reason.
- Identify and close scalability gaps in data stores across regions, cells, and deployment models.
- Build shared libraries that provide product teams with self-service storage capabilities.
- Partner closely with Cloud Platform, SRE, and DevEx teams.
- Raise the architectural bar across the organization and mentor Staff and Senior engineers.
- Apply AI tooling to data platform work, such as slow-query reviews and incident diagnosis.
Benefits
- Performance-based bonus may be offered.
- Equity may be offered.
- Generous benefits program.
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What This Job Offers
Job Type
Full-time
Career Level
Principal
Education Level
No Education Listed
